{
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Object Detection - Quick Start\n",
    "\n",
    ":label:`sec_object_detection_quick`\n",
    "\n",
    "\n",
    "Object detection is the process of identifying and localizing objects in an image and is an important task in computer vision. Follow this tutorial to learn how to use AutoGluon for object detection.\n",
    "\n",
    "**Tip**: If you are new to AutoGluon, review :ref:`sec_imgquick` first to learn the basics of the AutoGluon API.\n",
    "\n",
    "Our goal is to detect motorbike in images by [YOLO3 model](https://pjreddie.com/media/files/papers/YOLOv3.pdf). A tiny dataset is collected from VOC dataset, which only contains the motorbike category. The model pretrained on the COCO dataset is used to fine-tune our small dataset. With the help of AutoGluon, we are able to try many models with different hyperparameters automatically, and return the best one as our final model. \n",
    "\n",
    "To start, import autogluon and ObjectDetection module as your task:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import autogluon as ag\n",
    "from autogluon import ObjectDetection as task"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Tiny_motorbike Dataset\n",
    "We collect a toy dataset for detecting motorbikes in images. From the VOC dataset, images are randomly selected for training, validation, and testing - 120 images for training, 50 images for validation, and 50 for testing. This tiny dataset follows the same format as VOC. \n",
    "\n",
    "Using the commands below, we can download this dataset, which is only 23M. The variable `root` specifies the path to store the dataset in. The name of unzipped folder is called `tiny_motorbike`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Downloading ./tiny_motorbike.zip from https://autogluon.s3.amazonaws.com/datasets/tiny_motorbike.zip...\n"
     ]
    },
    {
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    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    }
   ],
   "source": [
    "root = './'\n",
    "filename_zip = ag.download('https://autogluon.s3.amazonaws.com/datasets/tiny_motorbike.zip',\n",
    "                        path=root)\n",
    "filename = ag.unzip(filename_zip, root=root)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "When we retrieve the dataset, we can create a dataset instance with its path and classes if it is a custom dataset."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      ">>> create dataset(VOC format) \n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "data_root = os.path.join(root, filename)\n",
    "dataset_train = task.Dataset(data_root, classes=('motorbike',))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Fit Models by AutoGluon\n",
    "In this section, we demonstrate how to apply AutoGluon to fit our detection models. We use mobilenet as the backbone for the YOLO3 model. Two different learning rates are used to fine-tune the network. The best model is the one that obtains the best performance on the validation dataset. You can also try using more networks and hyperparameters to create a larger searching space. \n",
    "\n",
    "We `fit` a classifier using AutoGluon as follows. In each experiment (one trial in our searching space), we train the model for 30 epoches."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Starting Experiments\n",
      "Num of Finished Tasks is 0\n",
      "Num of Pending Tasks is 2\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "scheduler: FIFOScheduler(\n",
      "DistributedResourceManager{\n",
      "(Remote: Remote REMOTE_ID: 0, \n",
      "\t<Remote: 'inproc://172.16.17.200/6491/1' processes=1 threads=8, memory=64.38 GB>, Resource: NodeResourceManager(8 CPUs, 1 GPUs))\n",
      "})\n",
      "\n"
     ]
    },
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     "output_type": "stream",
     "text": [
      "{'meta_arch': 'yolo3', 'dataset': <autogluon.task.object_detection.dataset.voc.CustomVOCDetection object at 0x7fa5681c8210>, 'net': 'mobilenet1.0', 'lr': 0.0005, 'loss': SoftmaxCrossEntropyLoss(batch_axis=0, w=None), 'num_gpus': 1, 'batch_size': 16, 'split_ratio': 0.8, 'epochs': 30, 'num_workers': 8, 'hybridize': True, 'verbose': False, 'final_fit': False, 'seed': 223, 'data_shape': 416, 'start_epoch': 0, 'transfer': 'coco', 'lr_mode': 'step', 'lr_decay': 0.1, 'lr_decay_period': 0, 'lr_decay_epoch': '160,180', 'warmup_lr': 0.0, 'warmup_epochs': 2, 'warmup_iters': 1000, 'warmup_factor': 0.3333333333333333, 'momentum': 0.9, 'wd': 0.0005, 'log_interval': 100, 'save_prefix': 'yolo3_mobilenet1.0_custom', 'save_interval': 10, 'val_interval': 1, 'num_samples': -1, 'no_random_shape': False, 'no_wd': False, 'mixup': False, 'no_mixup_epochs': 20, 'label_smooth': False, 'resume': '', 'syncbn': False, 'reuse_pred_weights': True, 'task_id': 0}\n",
      "[Epoch 0] Training cost: 4.055, ObjLoss=1944.205,BoxCenterLoss=3.516,BoxScaleLoss=2.340,ClassLoss=0.904\n",
      "[Epoch 0] Validation: motorbike=0.0 mAP=0.0\n",
      "[Epoch 1] Training cost: 3.780, ObjLoss=44.919,BoxCenterLoss=3.431,BoxScaleLoss=1.498,ClassLoss=0.832\n",
      "[Epoch 1] Validation: motorbike=0.12829318306853607 mAP=0.12829318306853607\n",
      "[Epoch 2] Training cost: 3.867, ObjLoss=35.371,BoxCenterLoss=3.290,BoxScaleLoss=1.243,ClassLoss=0.765\n",
      "[Epoch 2] Validation: motorbike=0.19423434113717816 mAP=0.19423434113717816\n",
      "[Epoch 3] Training cost: 2.687, ObjLoss=21.207,BoxCenterLoss=3.259,BoxScaleLoss=1.076,ClassLoss=0.655\n",
      "[Epoch 3] Validation: motorbike=0.3368144032367392 mAP=0.3368144032367392\n",
      "[Epoch 4] Training cost: 3.220, ObjLoss=18.045,BoxCenterLoss=3.484,BoxScaleLoss=1.031,ClassLoss=0.589\n",
      "[Epoch 4] Validation: motorbike=0.2545454545454545 mAP=0.2545454545454545\n",
      "[Epoch 5] Training cost: 3.631, ObjLoss=26.252,BoxCenterLoss=3.394,BoxScaleLoss=0.970,ClassLoss=0.511\n",
      "[Epoch 5] Validation: motorbike=0.30692829457364346 mAP=0.30692829457364346\n",
      "[Epoch 6] Training cost: 3.769, ObjLoss=15.006,BoxCenterLoss=3.289,BoxScaleLoss=0.932,ClassLoss=0.397\n",
      "[Epoch 6] Validation: motorbike=0.32401982401982404 mAP=0.32401982401982404\n",
      "[Epoch 7] Training cost: 3.221, ObjLoss=27.737,BoxCenterLoss=3.411,BoxScaleLoss=0.931,ClassLoss=0.395\n",
      "[Epoch 7] Validation: motorbike=0.30404499730667567 mAP=0.30404499730667567\n",
      "[Epoch 8] Training cost: 2.808, ObjLoss=50.132,BoxCenterLoss=3.447,BoxScaleLoss=1.014,ClassLoss=0.472\n",
      "[Epoch 8] Validation: motorbike=0.34014477343996796 mAP=0.34014477343996796\n",
      "[Epoch 9] Training cost: 3.833, ObjLoss=17.473,BoxCenterLoss=3.335,BoxScaleLoss=1.029,ClassLoss=0.331\n",
      "[Epoch 9] Validation: motorbike=0.4278493090623468 mAP=0.4278493090623468\n",
      "[Epoch 10] Training cost: 3.484, ObjLoss=10.012,BoxCenterLoss=3.325,BoxScaleLoss=0.813,ClassLoss=0.287\n",
      "[Epoch 10] Validation: motorbike=0.3910936807966511 mAP=0.3910936807966511\n",
      "[Epoch 11] Training cost: 3.365, ObjLoss=7.242,BoxCenterLoss=3.294,BoxScaleLoss=0.797,ClassLoss=0.275\n",
      "[Epoch 11] Validation: motorbike=0.513573591542404 mAP=0.513573591542404\n",
      "[Epoch 12] Training cost: 2.946, ObjLoss=7.643,BoxCenterLoss=3.335,BoxScaleLoss=0.811,ClassLoss=0.270\n",
      "[Epoch 12] Validation: motorbike=0.5282480786212129 mAP=0.5282480786212129\n",
      "[Epoch 13] Training cost: 3.888, ObjLoss=9.511,BoxCenterLoss=3.303,BoxScaleLoss=0.773,ClassLoss=0.232\n",
      "[Epoch 13] Validation: motorbike=0.40807109557109555 mAP=0.40807109557109555\n",
      "[Epoch 14] Training cost: 2.087, ObjLoss=31.395,BoxCenterLoss=3.335,BoxScaleLoss=0.941,ClassLoss=0.388\n",
      "[Epoch 14] Validation: motorbike=0.44724123213681255 mAP=0.44724123213681255\n",
      "[Epoch 15] Training cost: 2.304, ObjLoss=26.357,BoxCenterLoss=3.133,BoxScaleLoss=0.855,ClassLoss=0.319\n",
      "[Epoch 15] Validation: motorbike=0.48603326498063343 mAP=0.48603326498063343\n",
      "[Epoch 16] Training cost: 2.392, ObjLoss=12.680,BoxCenterLoss=3.161,BoxScaleLoss=0.712,ClassLoss=0.222\n",
      "[Epoch 16] Validation: motorbike=0.5062967335694608 mAP=0.5062967335694608\n",
      "[Epoch 17] Training cost: 2.736, ObjLoss=12.246,BoxCenterLoss=3.121,BoxScaleLoss=0.815,ClassLoss=0.246\n",
      "[Epoch 17] Validation: motorbike=0.5878787878787878 mAP=0.5878787878787878\n",
      "[Epoch 18] Training cost: 2.780, ObjLoss=11.712,BoxCenterLoss=3.215,BoxScaleLoss=0.813,ClassLoss=0.217\n",
      "[Epoch 18] Validation: motorbike=0.5543411134320225 mAP=0.5543411134320225\n",
      "[Epoch 19] Training cost: 2.407, ObjLoss=10.965,BoxCenterLoss=3.138,BoxScaleLoss=0.743,ClassLoss=0.203\n",
      "[Epoch 19] Validation: motorbike=0.6055813382756715 mAP=0.6055813382756715\n",
      "[Epoch 20] Training cost: 2.218, ObjLoss=9.788,BoxCenterLoss=3.290,BoxScaleLoss=0.785,ClassLoss=0.220\n",
      "[Epoch 20] Validation: motorbike=0.6190006121824304 mAP=0.6190006121824304\n",
      "[Epoch 21] Training cost: 2.203, ObjLoss=10.389,BoxCenterLoss=3.164,BoxScaleLoss=0.784,ClassLoss=0.270\n",
      "[Epoch 21] Validation: motorbike=0.6088888400209155 mAP=0.6088888400209155\n",
      "[Epoch 22] Training cost: 2.899, ObjLoss=7.730,BoxCenterLoss=3.312,BoxScaleLoss=0.686,ClassLoss=0.193\n",
      "[Epoch 22] Validation: motorbike=0.5650605609795026 mAP=0.5650605609795026\n",
      "[Epoch 23] Training cost: 3.503, ObjLoss=8.411,BoxCenterLoss=3.225,BoxScaleLoss=0.780,ClassLoss=0.163\n",
      "[Epoch 23] Validation: motorbike=0.6553147991649054 mAP=0.6553147991649054\n",
      "[Epoch 24] Training cost: 2.376, ObjLoss=8.171,BoxCenterLoss=3.331,BoxScaleLoss=0.806,ClassLoss=0.229\n",
      "[Epoch 24] Validation: motorbike=0.5520845736040982 mAP=0.5520845736040982\n",
      "[Epoch 25] Training cost: 2.749, ObjLoss=8.383,BoxCenterLoss=3.338,BoxScaleLoss=0.887,ClassLoss=0.258\n",
      "[Epoch 25] Validation: motorbike=0.6081130485155254 mAP=0.6081130485155254\n",
      "[Epoch 26] Training cost: 2.070, ObjLoss=6.994,BoxCenterLoss=3.128,BoxScaleLoss=0.770,ClassLoss=0.223\n",
      "[Epoch 26] Validation: motorbike=0.6564246762760015 mAP=0.6564246762760015\n",
      "[Epoch 27] Training cost: 2.303, ObjLoss=4.991,BoxCenterLoss=3.213,BoxScaleLoss=0.729,ClassLoss=0.222\n",
      "[Epoch 27] Validation: motorbike=0.6339876381240478 mAP=0.6339876381240478\n",
      "[Epoch 28] Training cost: 2.487, ObjLoss=5.365,BoxCenterLoss=3.288,BoxScaleLoss=0.766,ClassLoss=0.201\n",
      "[Epoch 28] Validation: motorbike=0.6610689345890192 mAP=0.6610689345890192\n",
      "[Epoch 29] Training cost: 2.723, ObjLoss=5.011,BoxCenterLoss=3.293,BoxScaleLoss=0.793,ClassLoss=0.182\n",
      "[Epoch 29] Validation: motorbike=0.6391805488932712 mAP=0.6391805488932712\n",
      "Finished Task with config: {'lr.choice': 0, 'net.choice': 0} and reward: 0.6391805488932712\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "{'meta_arch': 'yolo3', 'dataset': <autogluon.task.object_detection.dataset.voc.CustomVOCDetection object at 0x7fa5681e3710>, 'net': 'mobilenet1.0', 'lr': 0.0001, 'loss': SoftmaxCrossEntropyLoss(batch_axis=0, w=None), 'num_gpus': 1, 'batch_size': 16, 'split_ratio': 0.8, 'epochs': 30, 'num_workers': 8, 'hybridize': True, 'verbose': False, 'final_fit': False, 'seed': 223, 'data_shape': 416, 'start_epoch': 0, 'transfer': 'coco', 'lr_mode': 'step', 'lr_decay': 0.1, 'lr_decay_period': 0, 'lr_decay_epoch': '160,180', 'warmup_lr': 0.0, 'warmup_epochs': 2, 'warmup_iters': 1000, 'warmup_factor': 0.3333333333333333, 'momentum': 0.9, 'wd': 0.0005, 'log_interval': 100, 'save_prefix': 'yolo3_mobilenet1.0_custom', 'save_interval': 10, 'val_interval': 1, 'num_samples': -1, 'no_random_shape': False, 'no_wd': False, 'mixup': False, 'no_mixup_epochs': 20, 'label_smooth': False, 'resume': '', 'syncbn': False, 'reuse_pred_weights': True, 'task_id': 1}\n",
      "[Epoch 0] Training cost: 3.954, ObjLoss=2026.853,BoxCenterLoss=3.704,BoxScaleLoss=2.862,ClassLoss=1.006\n",
      "[Epoch 0] Validation: motorbike=0.0 mAP=0.0\n",
      "[Epoch 1] Training cost: 3.866, ObjLoss=19.717,BoxCenterLoss=3.496,BoxScaleLoss=2.105,ClassLoss=0.927\n",
      "[Epoch 1] Validation: motorbike=0.0 mAP=0.0\n",
      "[Epoch 2] Training cost: 3.943, ObjLoss=15.818,BoxCenterLoss=3.352,BoxScaleLoss=1.471,ClassLoss=0.706\n",
      "[Epoch 2] Validation: motorbike=0.09090909090909091 mAP=0.09090909090909091\n",
      "[Epoch 3] Training cost: 2.758, ObjLoss=17.481,BoxCenterLoss=3.371,BoxScaleLoss=1.491,ClassLoss=0.666\n",
      "[Epoch 3] Validation: motorbike=0.28323806011432784 mAP=0.28323806011432784\n",
      "[Epoch 4] Training cost: 3.382, ObjLoss=10.441,BoxCenterLoss=3.485,BoxScaleLoss=1.266,ClassLoss=0.658\n",
      "[Epoch 4] Validation: motorbike=0.3336666213402378 mAP=0.3336666213402378\n",
      "[Epoch 5] Training cost: 3.503, ObjLoss=8.163,BoxCenterLoss=3.324,BoxScaleLoss=1.061,ClassLoss=0.607\n",
      "[Epoch 5] Validation: motorbike=0.2904398711196456 mAP=0.2904398711196456\n",
      "[Epoch 6] Training cost: 3.814, ObjLoss=6.745,BoxCenterLoss=3.072,BoxScaleLoss=0.896,ClassLoss=0.513\n",
      "[Epoch 6] Validation: motorbike=0.41333896455847674 mAP=0.41333896455847674\n",
      "[Epoch 7] Training cost: 3.348, ObjLoss=9.732,BoxCenterLoss=3.178,BoxScaleLoss=0.934,ClassLoss=0.521\n",
      "[Epoch 7] Validation: motorbike=0.5077472758091708 mAP=0.5077472758091708\n",
      "[Epoch 8] Training cost: 2.625, ObjLoss=12.339,BoxCenterLoss=3.208,BoxScaleLoss=1.059,ClassLoss=0.556\n",
      "[Epoch 8] Validation: motorbike=0.5452210955481662 mAP=0.5452210955481662\n",
      "[Epoch 9] Training cost: 3.830, ObjLoss=9.099,BoxCenterLoss=3.235,BoxScaleLoss=0.957,ClassLoss=0.479\n",
      "[Epoch 9] Validation: motorbike=0.5872699601153774 mAP=0.5872699601153774\n",
      "[Epoch 10] Training cost: 3.359, ObjLoss=9.402,BoxCenterLoss=3.210,BoxScaleLoss=0.863,ClassLoss=0.445\n",
      "[Epoch 10] Validation: motorbike=0.5751097418621864 mAP=0.5751097418621864\n",
      "[Epoch 11] Training cost: 3.675, ObjLoss=6.874,BoxCenterLoss=3.318,BoxScaleLoss=0.881,ClassLoss=0.424\n",
      "[Epoch 11] Validation: motorbike=0.5650427285324645 mAP=0.5650427285324645\n",
      "[Epoch 12] Training cost: 3.055, ObjLoss=7.118,BoxCenterLoss=3.277,BoxScaleLoss=0.764,ClassLoss=0.434\n",
      "[Epoch 12] Validation: motorbike=0.6309218394381509 mAP=0.6309218394381509\n",
      "[Epoch 13] Training cost: 3.989, ObjLoss=5.754,BoxCenterLoss=3.312,BoxScaleLoss=0.820,ClassLoss=0.413\n",
      "[Epoch 13] Validation: motorbike=0.6388263699952202 mAP=0.6388263699952202\n",
      "[Epoch 14] Training cost: 2.135, ObjLoss=9.336,BoxCenterLoss=3.435,BoxScaleLoss=1.106,ClassLoss=0.546\n",
      "[Epoch 14] Validation: motorbike=0.6882508454886971 mAP=0.6882508454886971\n",
      "[Epoch 15] Training cost: 2.230, ObjLoss=7.855,BoxCenterLoss=3.175,BoxScaleLoss=0.941,ClassLoss=0.492\n",
      "[Epoch 15] Validation: motorbike=0.6538358955841171 mAP=0.6538358955841171\n",
      "[Epoch 16] Training cost: 2.383, ObjLoss=4.948,BoxCenterLoss=3.042,BoxScaleLoss=0.760,ClassLoss=0.345\n",
      "[Epoch 16] Validation: motorbike=0.6785833511376991 mAP=0.6785833511376991\n",
      "[Epoch 17] Training cost: 2.822, ObjLoss=6.354,BoxCenterLoss=3.107,BoxScaleLoss=0.902,ClassLoss=0.426\n",
      "[Epoch 17] Validation: motorbike=0.6972976572544564 mAP=0.6972976572544564\n",
      "[Epoch 18] Training cost: 2.714, ObjLoss=4.820,BoxCenterLoss=3.223,BoxScaleLoss=0.791,ClassLoss=0.364\n",
      "[Epoch 18] Validation: motorbike=0.703144375075953 mAP=0.703144375075953\n",
      "[Epoch 19] Training cost: 2.518, ObjLoss=4.926,BoxCenterLoss=3.280,BoxScaleLoss=0.813,ClassLoss=0.414\n",
      "[Epoch 19] Validation: motorbike=0.6731428402801163 mAP=0.6731428402801163\n",
      "[Epoch 20] Training cost: 2.307, ObjLoss=5.014,BoxCenterLoss=3.225,BoxScaleLoss=0.767,ClassLoss=0.407\n",
      "[Epoch 20] Validation: motorbike=0.6265080573565658 mAP=0.6265080573565658\n",
      "[Epoch 21] Training cost: 2.345, ObjLoss=4.822,BoxCenterLoss=3.118,BoxScaleLoss=0.813,ClassLoss=0.438\n",
      "[Epoch 21] Validation: motorbike=0.6188945369589427 mAP=0.6188945369589427\n",
      "[Epoch 22] Training cost: 2.830, ObjLoss=4.313,BoxCenterLoss=3.294,BoxScaleLoss=0.717,ClassLoss=0.357\n",
      "[Epoch 22] Validation: motorbike=0.6844070242375327 mAP=0.6844070242375327\n",
      "[Epoch 23] Training cost: 3.673, ObjLoss=4.442,BoxCenterLoss=3.184,BoxScaleLoss=0.772,ClassLoss=0.297\n",
      "[Epoch 23] Validation: motorbike=0.7837793478312701 mAP=0.7837793478312701\n",
      "[Epoch 24] Training cost: 2.440, ObjLoss=4.708,BoxCenterLoss=3.130,BoxScaleLoss=0.735,ClassLoss=0.360\n",
      "[Epoch 24] Validation: motorbike=0.7230004894181464 mAP=0.7230004894181464\n",
      "[Epoch 25] Training cost: 2.634, ObjLoss=4.608,BoxCenterLoss=3.090,BoxScaleLoss=0.848,ClassLoss=0.380\n",
      "[Epoch 25] Validation: motorbike=0.6597934261929371 mAP=0.6597934261929371\n",
      "[Epoch 26] Training cost: 2.223, ObjLoss=4.543,BoxCenterLoss=3.327,BoxScaleLoss=0.869,ClassLoss=0.451\n",
      "[Epoch 26] Validation: motorbike=0.7040029514127943 mAP=0.7040029514127943\n",
      "[Epoch 27] Training cost: 2.445, ObjLoss=4.515,BoxCenterLoss=3.105,BoxScaleLoss=0.736,ClassLoss=0.379\n",
      "[Epoch 27] Validation: motorbike=0.7266402645202658 mAP=0.7266402645202658\n",
      "[Epoch 28] Training cost: 2.445, ObjLoss=3.990,BoxCenterLoss=3.195,BoxScaleLoss=0.826,ClassLoss=0.330\n",
      "[Epoch 28] Validation: motorbike=0.7137933587005023 mAP=0.7137933587005023\n",
      "[Epoch 29] Training cost: 2.878, ObjLoss=4.518,BoxCenterLoss=3.187,BoxScaleLoss=0.769,ClassLoss=0.334\n",
      "[Epoch 29] Validation: motorbike=0.8069742780549053 mAP=0.8069742780549053\n",
      "Finished Task with config: {'lr.choice': 1, 'net.choice': 0} and reward: 0.8069742780549053\n",
      "{'meta_arch': 'yolo3', 'dataset': <autogluon.task.object_detection.dataset.voc.CustomVOCDetection object at 0x7fa56ba2e4d0>, 'net': 'mobilenet1.0', 'lr': 0.0001, 'loss': SoftmaxCrossEntropyLoss(batch_axis=0, w=None), 'num_gpus': 1, 'batch_size': 16, 'split_ratio': 0.8, 'epochs': 30, 'num_workers': 8, 'hybridize': True, 'verbose': False, 'final_fit': True, 'seed': 223, 'data_shape': 416, 'start_epoch': 0, 'transfer': 'coco', 'lr_mode': 'step', 'lr_decay': 0.1, 'lr_decay_period': 0, 'lr_decay_epoch': '160,180', 'warmup_lr': 0.0, 'warmup_epochs': 2, 'warmup_iters': 1000, 'warmup_factor': 0.3333333333333333, 'momentum': 0.9, 'wd': 0.0005, 'log_interval': 100, 'save_prefix': 'yolo3_mobilenet1.0_custom', 'save_interval': 10, 'val_interval': 1, 'num_samples': -1, 'no_random_shape': False, 'no_wd': False, 'mixup': False, 'no_mixup_epochs': 20, 'label_smooth': False, 'resume': '', 'syncbn': False, 'reuse_pred_weights': True, 'task_id': 2}\n",
      "[Epoch 0] Training cost: 2.823, ObjLoss=713.012,BoxCenterLoss=3.944,BoxScaleLoss=2.999,ClassLoss=1.029\n",
      "[Epoch 1] Training cost: 3.028, ObjLoss=15.467,BoxCenterLoss=3.767,BoxScaleLoss=2.109,ClassLoss=0.893\n",
      "[Epoch 2] Training cost: 3.763, ObjLoss=13.988,BoxCenterLoss=4.024,BoxScaleLoss=1.785,ClassLoss=0.794\n",
      "[Epoch 3] Training cost: 4.555, ObjLoss=10.369,BoxCenterLoss=3.742,BoxScaleLoss=1.525,ClassLoss=0.669\n",
      "[Epoch 4] Training cost: 3.413, ObjLoss=8.473,BoxCenterLoss=3.695,BoxScaleLoss=1.333,ClassLoss=0.680\n",
      "[Epoch 5] Training cost: 3.845, ObjLoss=6.875,BoxCenterLoss=3.635,BoxScaleLoss=1.173,ClassLoss=0.535\n",
      "[Epoch 6] Training cost: 3.728, ObjLoss=6.954,BoxCenterLoss=3.697,BoxScaleLoss=1.208,ClassLoss=0.496\n",
      "[Epoch 7] Training cost: 3.290, ObjLoss=6.389,BoxCenterLoss=3.648,BoxScaleLoss=1.244,ClassLoss=0.566\n",
      "[Epoch 8] Training cost: 4.166, ObjLoss=6.438,BoxCenterLoss=3.827,BoxScaleLoss=1.178,ClassLoss=0.472\n",
      "[Epoch 9] Training cost: 3.720, ObjLoss=5.546,BoxCenterLoss=3.573,BoxScaleLoss=1.137,ClassLoss=0.408\n",
      "[Epoch 10] Training cost: 2.943, ObjLoss=5.214,BoxCenterLoss=3.487,BoxScaleLoss=1.105,ClassLoss=0.437\n",
      "[Epoch 11] Training cost: 3.575, ObjLoss=5.489,BoxCenterLoss=3.617,BoxScaleLoss=0.942,ClassLoss=0.421\n",
      "[Epoch 12] Training cost: 3.739, ObjLoss=5.135,BoxCenterLoss=3.559,BoxScaleLoss=0.991,ClassLoss=0.355\n",
      "[Epoch 13] Training cost: 4.105, ObjLoss=5.486,BoxCenterLoss=3.532,BoxScaleLoss=0.916,ClassLoss=0.293\n",
      "[Epoch 14] Training cost: 4.115, ObjLoss=5.481,BoxCenterLoss=3.609,BoxScaleLoss=1.007,ClassLoss=0.335\n",
      "[Epoch 15] Training cost: 3.077, ObjLoss=4.901,BoxCenterLoss=3.530,BoxScaleLoss=1.020,ClassLoss=0.328\n",
      "[Epoch 16] Training cost: 2.703, ObjLoss=5.401,BoxCenterLoss=3.687,BoxScaleLoss=1.027,ClassLoss=0.414\n",
      "[Epoch 17] Training cost: 2.702, ObjLoss=4.802,BoxCenterLoss=3.608,BoxScaleLoss=0.908,ClassLoss=0.387\n",
      "[Epoch 18] Training cost: 3.851, ObjLoss=5.474,BoxCenterLoss=3.604,BoxScaleLoss=0.888,ClassLoss=0.264\n",
      "[Epoch 19] Training cost: 2.897, ObjLoss=4.703,BoxCenterLoss=3.597,BoxScaleLoss=0.969,ClassLoss=0.371\n",
      "[Epoch 20] Training cost: 3.656, ObjLoss=4.583,BoxCenterLoss=3.537,BoxScaleLoss=0.909,ClassLoss=0.302\n",
      "[Epoch 21] Training cost: 3.242, ObjLoss=4.441,BoxCenterLoss=3.592,BoxScaleLoss=0.789,ClassLoss=0.244\n",
      "[Epoch 22] Training cost: 3.523, ObjLoss=4.354,BoxCenterLoss=3.392,BoxScaleLoss=0.858,ClassLoss=0.264\n",
      "[Epoch 23] Training cost: 3.435, ObjLoss=4.283,BoxCenterLoss=3.498,BoxScaleLoss=0.861,ClassLoss=0.281\n",
      "[Epoch 24] Training cost: 3.473, ObjLoss=4.710,BoxCenterLoss=3.465,BoxScaleLoss=0.877,ClassLoss=0.230\n",
      "[Epoch 25] Training cost: 4.339, ObjLoss=4.364,BoxCenterLoss=3.454,BoxScaleLoss=0.783,ClassLoss=0.182\n",
      "[Epoch 26] Training cost: 3.467, ObjLoss=4.392,BoxCenterLoss=3.573,BoxScaleLoss=0.901,ClassLoss=0.218\n",
      "[Epoch 27] Training cost: 3.677, ObjLoss=4.006,BoxCenterLoss=3.340,BoxScaleLoss=0.808,ClassLoss=0.196\n",
      "[Epoch 28] Training cost: 4.262, ObjLoss=4.778,BoxCenterLoss=3.411,BoxScaleLoss=0.892,ClassLoss=0.183\n",
      "[Epoch 29] Training cost: 2.719, ObjLoss=4.454,BoxCenterLoss=3.367,BoxScaleLoss=0.838,ClassLoss=0.238\n",
      "Saving Training Curve in checkpoint/plot_training_curves.png\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      ">>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> finish model fitting\n",
      "The best config: {'lr.choice': 1, 'net.choice': 0}\n"
     ]
    }
   ],
   "source": [
    "time_limits = 5*60*60  # 5 hours\n",
    "epochs = 30\n",
    "detector = task.fit(dataset_train,\n",
    "                    num_trials=2,\n",
    "                    epochs=epochs,\n",
    "                    lr=ag.Categorical(5e-4, 1e-4),\n",
    "                    ngpus_per_trial=1,\n",
    "                    time_limits=time_limits)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "After fitting, AutoGluon automatically returns the best model among all models in the searching space. From the output, we know the best model is the one trained with the second learning rate. To see how well the returned model performed on test dataset, call detector.evaluate()."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      ">>> create dataset(VOC format) \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "mAP on test dataset: 0.8360411011140064\n"
     ]
    }
   ],
   "source": [
    "dataset_test = task.Dataset(data_root, index_file_name='test', classes=('motorbike',))\n",
    "\n",
    "test_map = detector.evaluate(dataset_test)\n",
    "print(\"mAP on test dataset: {}\".format(test_map[1][1]))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Below, we randomly select an image from test dataset and show the predicted box and probability over the origin image."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "image = '000467.jpg'\n",
    "image_path = os.path.join(data_root, 'JPEGImages', image)\n",
    "\n",
    "ind, prob, loc = detector.predict(image_path)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "conda_autogluon",
   "language": "python",
   "name": "conda_autogluon"
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   "file_extension": ".py",
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   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
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